3 citations · 3 across the 4 of their papers we have counts for
9 papers
CounselBench: A Large-Scale Expert Evaluation and Adversarial Benchmarking of Large Language Models in Mental Health Question Answering
Yahan Li, Jifan Yao, John Bosco S. Bunyi +3
Medical question answering (QA) benchmarks often focus on multiple-choice or fact-based tasks, leaving open-ended answers to real patient questions underexplored. This gap is parti…
MedExAgent: Training LLM Agents to Ask, Examine, and Diagnose in Noisy Clinical Environments
Yicheng Gao, Xiaolin Zhou, Yahan Li +2
Real-world clinical diagnosis is a complex process in which the doctor is required to obtain information from both interaction with the patient and conducting medical exams. Additi…
CounselReflect: A Toolkit for Auditing Mental-Health Dialogues
Yahan Li, Chaohao Du, Zeyang Li +5
Mental-health support is increasingly mediated by conversational systems (e.g., LLM-based tools), but users often lack structured ways to audit the quality and potential risks of t…
Beyond Idealized Patients: Evaluating LLMs under Challenging Patient Behaviors in Medical Consultations
Yahan Li, Xinyi Jie, Wanjia Ruan +5
Large language models (LLMs) are increasingly used for medical consultation and health information support. In this high-stakes setting, safety depends not only on medical knowledg…
VoiceAgentEval: A Dual-Dimensional Benchmark for Expert-Level Intelligent Voice-Agent Evaluation of Xbench's Professional-Aligned Series
Pengyu Xu, Shijia Li, Ao Sun +15
We propose OutboundEval, a comprehensive benchmark for evaluating large language models (LLMs) in expert-level intelligent outbound calling scenarios. Unlike existing methods that…
Hierarchical Structure-Property Alignment for Data-Efficient Molecular Generation and Editing
Ziyu Fan, Zhijian Huang, Yahan Li +9
Property-constrained molecular generation and editing are crucial in AI-driven drug discovery but remain hindered by two factors: (i) capturing the complex relationships between mo…